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Books > Computing & IT > Applications of computing > Artificial intelligence > General
Created with the input of a distinguished International Board of
the foremost authorities in data mining from academia and industry,
"The Handbook of Data Mining" presents comprehensive coverage of
data mining concepts and techniques. Algorithms, methodologies,
management issues, and tools are all illustrated through engaging
examples and real-world applications to ease understanding of the
materials.
Artificial intelligence (AI) and digital engineering have become prevalent in business, industry, government, and academia. However, the workforce still has a lot to learn on how to leverage them. This handbook presents the preparatory and operational foundations for the efficacy, applicability, risk, and how to take advantage of these tools and techniques. "Handbook of Mathematical and Digital Engineering Foundations for Artificial Intelligence: A Systems Methodology" provides a guide for using digital engineering platforms for advancing AI applications. The book discusses an interface of education and research in the pursuit of AI developments and highlights the facilitation of advanced education through AI and digital engineering systems. It presents an integration of soft and hard skills in developing and using AI and offers a rigorous systems approach to understanding and using AI. This handbook will be the go-to resource for practitioners and students on applying systems methodology to the body of knowledge of understanding, embracing, and using digital engineering tools and techniques.
Presents sensor specification, theory of operation, sensor design, and application criteria Provides background plus specific information for practicing engineers who want to understand sensors Includes a complete chapter on industrial sensor communication protocols Explains temperature sensitivity, how to determine, and how to avoid Discusses how to understand and utilize sensor specifications
Over the last 20 years, approaches to designing speech and language processing algorithms have moved from methods based on linguistics and speech science to data-driven pattern recognition techniques. These techniques have been the focus of intense, fast-moving research and have contributed to significant advances in this field.
As data is an important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization. This volume of a two-volume handbook set provides a roadmap for new trends and future developments of data science with semantic technologies. Data Science with Semantic Technologies: New Trends and Future Developments highlights how data science enables the user to create intelligence through these technologies. In addition, this book offers the answers to various questions such as can semantic technologies be able to facilitate data science? Which type of data science problems can be tackled by semantic technologies? How can data scientists get benefited from these technologies? What is the role of semantic technologies in data science? What is the current progress and future of data science with semantic technologies? Which types of problems require the immediate attention of the researchers? What should be the vision 2030 for data science? This volume can serve as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for scholars, researchers, professionals, and practitioners in this field.
Gone are the days when data was interlinked with related data by humans and to find insights coherently, human interpretation was required. Data is no more just data. It is now considered a Thing or Entity or Concept- to bring the meaning to it, so that a machine not only understands the concept but also extrapolates the way humans do. Data Science with Semantic Technologies: Deployment and Exploration volume of a two-volume handbook set provides a roadmap for the deployment of semantic technologies in the field of data science and enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition, this book offers the answer to various questions like What makes a technology semantic as opposed to other approaches to data science? What is knowledge data science? How does knowledge data science relate to other fields? This book explores the optimal use of these technologies to provide the highest benefit to the user under one comprehensive source and title. As there is no dedicated book available in the market on this topic at this time, this proposed new book becomes a unique and only resource for scholars, researchers, data scientists, professionals, and practitioners. This volume can serve as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for scholars, researchers, professionals, and practitioners in this field.
Language resources and computational models are becoming increasingly important for the study of language variation. A main challenge of this interdisciplinary field is that linguistics researchers may not be familiar with these helpful computational tools and many NLP researchers are often not familiar with language variation phenomena. This essential reference introduces researchers to the necessary computational models for processing similar languages, varieties, and dialects. In this book, leading experts tackle the inherent challenges of the field by balancing a thorough discussion of the theoretical background with a meaningful overview of state-of-the-art language technology. The book can be used in a graduate course, or as a supplementary text for courses on language variation, dialectology, and sociolinguistics or on computational linguistics and NLP. Part 1 covers the linguistic fundamentals of the field such as the question of status and language variation. Part 2 discusses data collection and pre-processing methods. Finally, Part 3 presents NLP applications such as speech processing, machine translation, and language-specific issues in Arabic and Chinese.
Provides theoretical and practical knowledge about swarm intelligence and evolutionary computation. Covers interdisciplinary research topics that encompass problem-solving tasks in AI and deep learning in an easy-to-understand manner. Describes a framework (i.e., deep neuroevolution and deep swarms) that integrates swarm intelligence and evolutionary computation with deep learning. Reviews researches in AI from the past to the present and considers the future progress of AI, based on the ideas of swarm intelligence and evolution. Shows how to learn practical tasks by neuroevolution with an AI educational software, MindRender.
The International Conference on Information Processing and Management of - certainty in Knowledge-Based Systems, IPMU, is organized every two years with the aim of bringing together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. Since 1986, this conference has been providing a forum for the exchange of ideas between th theoreticians and practitioners working in these areas and related ?elds. The 13 IPMU conference took place in Dortmund, Germany, June 28-July 2, 2010. This volume contains 79 papers selected through a rigorous reviewing process. The contributions re?ect the richness of research on topics within the scope of the conference and represent several important developments, speci?cally focused on theoretical foundations and methods for information processing and management of uncertainty in knowledge-based systems. We were delighted that Melanie Mitchell (Portland State University, USA), Nihkil R. Pal (Indian Statistical Institute), Bernhard Sch olkopf (Max Planck I- titute for Biological Cybernetics, Tubing en, Germany) and Wolfgang Wahlster (German Research Center for Arti?cial Intelligence, Saarbruc ken) accepted our invitations to present keynote lectures. Jim Bezdek received the Kampede F eriet Award, granted every two years on the occasion of the IPMU conference, in view of his eminent research contributions to the handling of uncertainty in clustering, data analysis and pattern recognition.
This book presents comparative design as an approach to the conceptual design of structures. Primarily focusing on reasonable structural performance, sustainable development and architectural aesthetics, it features detailed studies of structural performance through the composition and de-composition of these elements for a variety of structures, such as high-rise buildings, long-span crossings and spatial structures. The latter part of the book addresses the theoretical basis and practical implementation of knowledge engineering in structural design, and a case-based fuzzy reasoning method is introduced to illustrate the concept and method of intelligent design. The book is intended for civil engineers, structural designers and architects, as well as senior undergraduate and graduate students in civil engineering and architecture. Lin Shaopei and Huang Zhen are both Professors at the Department of Civil Engineering, Shanghai Jiao Tong University, China.
This volume constitutes the refereed proceedings of the 3rd International Conference on Advanced Communication and Networking, ACN 2011, held in Brno, Czech Republik, in June 2011. The 57 revised full papers presented in this volume were carefully reviewed and selected from numerous submissions. The papers focus on the various aspects of progress in Advanced Communication and Networking with computational sciences, mathematics and information technology and address all current issues of communication basic and infrastructure, networks basic and management, multimedia application, image, video, signal and information processing.
The Routledge Handbook of FinTech offers comprehensive coverage of the opportunities, challenges and future trends of financial technology. This handbook is a unique and in-depth reference work. It is organised in six thematic parts. The first part outlines the development, funding, and the future trends. The second focuses on blockchain technology applications and various aspects of cryptocurrencies. The next covers FinTech in banking. A significant element of FinTech, mobile payments and online lending, is included in the fourth part. The fifth continues with several chapters covering other financial services, while the last discusses ethics and regulatory issues. These six parts represent the most significant and overarching themes of FinTech innovations. This handbook will appeal to students, established researchers seeking a single repository on the subject, as well as policy makers and market professionals seeking convenient access to a one-stop guide.
Designed to offer an accessible set of case studies and analyses of ethical dilemmas in data science. This book will be suitable for technical readers in data science who want to understand diverse ethical approaches to AI.
Gives broad perspective on 5G communications with a focus on smart cities Discusses artificial intelligence in future wireless communication and its applications Provides a systemic and comprehensive coverage of 6G technologies, challenges and use cases Explores role of future wireless in safety, health, and transport in smart cities Includes case studies of future wireless communications
Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners.
This book systematically introduces the bionic nature of force sensing and control, the biomechanical principle on mechanism of force generation and control of skeletal muscle, and related applications in robotic exoskeleton. The book focuses on three main aspects: muscle force generation principle and biomechanical model, exoskeleton robot technology based on skeletal muscle biomechanical model, and SMA-based bionic skeletal muscle technology. This comprehensive and in-depth book presents the author's research experience and achievements of many years to readers in an effort to promote academic exchanges in this field. About the Author Yuehong Yin received his B.E. , M.S. and Ph.D. degrees from Nanjing University of Aeronautics and Astronautics, Nanjing, in 1990, 1995 and 1997, respectively, all in mechanical engineering. From December 1997 to December 1999, he was a Postdoctoral Fellow with Zhejiang University, Hangzhou, China, where he became an Associate Professor in July 1999. Since December 1999, he has been with the Robotics Institute, Shanghai Jiao Tong University, Shanghai, China, where he became a Professor and a Tenure Professor in December 2005 and January 2016, respectively. His research interests include robotics, force control, exoskeleton robot, molecular motor, artificial limb, robotic assembly, reconfigurable assembly system, and augmented reality. Dr. Yin is a fellow of the International Academy of Production Engineering (CIRP).
This book provides insights on how to approach and utilize data science tools, technologies and methodologies related to artificial intelligence (AI) in industrial contexts. It explains the essence of distributed computing and AI-technologies, and their inter-connections. Description of various technology and methodology approaches, and their purpose and benefits when developing AI-solution in industrial contexts is included. In addition, it summarizes experiences from AI technology deployment projects from several industrial sectors. Features: Presents compendium of methodologies and technologies in Industrial AI and digitalization. Illustrates sensor to actuation approach showing complete cycle, that defines and differences AI and digitalization concept. Covers a broad range of academic and industrial issues within the field of asset management. Discusses impact of Industry 4.0 in other sectors. Includes a dedicated chapter on real-time case studies. This book is aimed at researchers and professionals in industrial and software engineering, network security, AI and ML, engineering managers, operational and maintenance specialists, asset managers, digital and AI manufacturing specialists.
The text focuses on mathematical modeling and applications of advanced techniques of machine learning, and artificial intelligence, including artificial neural networks, evolutionary computing, data mining, and fuzzy systems to solve performance and design issues more precisely. Intelligent computing encompasses technologies, algorithms, and models in providing effective and efficient solutions to a wide range of problems including the airport's intelligent safety system. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields including industrial engineering, manufacturing engineering, computer engineering, and mathematics. The book- Discusses mathematical modeling for traffic, sustainable supply chain, vehicular Ad-Hoc networks, internet of things networks with intelligent gateways. Covers advanced machine learning, artificial intelligence, fuzzy systems, evolutionary computing, data mining techniques for real-world problems. Presents applications of mathematical models in chronic diseases such as kidney and coronary artery diseases. Highlights advances in mathematical modeling, strength, and benefits of machine learning and artificial intelligence, including driving goals, applicability, algorithms, and processes involved. Showcases emerging real-life topics on mathematical models, machine learning, and intelligent computing using an interdisciplinary approach. The text presents emerging real-life topics on mathematical models, machine learning, and intelligent computing in a single volume. It will serve as an ideal text for senior undergraduate, graduate students, and researchers in diverse fields domains including industrial and manufacturing engineering, computer engineering, and mathematics.
This book is a compilation of selected papers from the 4th ENRI International Workshop on ATM/CNS (EIWAC2015). The work focuses on novel techniques for aviation infrastructure in air traffic management (ATM) and communications, navigation, surveillance, and informatics (CNSI) domains. The contents make valuable contributions to academic researchers, engineers in the industry, and regulators of aviation authorities. As well, readers will encounter new ideas for realizing a more efficient and safer aviation system.
The last decade has seen dramatic advances in artificial intelligence and robotics technology, raising tough questions that need to be addressed. The Robot Will See You Now considers how Christians can respond to these issues - and flourish - in the years ahead. Contributions from a number of international experts, including editors John Wyatt and Stephen Williams, explore a range of social and ethical issues raised by recent advances in AI and robotics. Considering the role of artificial intelligence in areas such as medicine, employment and security, the book looks at how AI is perceived as well as its actual impact on human interactions and relationships. Alongside are theological responses from an orthodox Christian perspective. Looking at how artificial intelligence and robotics may be considered in the light of Christian doctrine, The Robot Will See You Now offers a measured, thoughtful view on how Christians can understand and prepare for the challenges posted by the development of AI. This is a book for anyone who is interested in learning more about how AI and robots have advanced in recent years, and anyone who has wondered how Christian teaching relates to artificial intelligence. Whatever your level of technical knowledge, The Robot Will See You Now will give you a thorough understanding of AI and equip you to respond to the challenges it poses with confidence and faith.
This CCIS volume constitutes the proceedings of the First International Conference on Computational Systems Biology and Bioinformatics (CSBio 2010), held in Bangkok, Thailand, November 3-5, 2010. CSBio 2010 was a follow up to the successful Special th Session on Computational Advances in Bioinformatics (CAB 2009) in the 16 International Conference on Neural Information Processing (ICONIP 2009). CSBio will provide an annual forum for international researchers to exchange the latest ideas on advances in the interdisciplinary fields of computational systems biology and bioinformatics. CSBio is proposed to be hosted alternately by King Mongkut's University of Technology Thonburi (KMUTT), Thailand, and Nanyang Technological University (NTU), Singapore. The School of Information Technology (SIT) at KMUTT was the proud host of CSBio 2010. This inaugural conference was launched th th to coincide with the 15 anniversary of SIT and the 50 anniversary of KMUTT. CSBio 2010 accepted 19 regular session papers from a total of 48 submissions received on the EasyChair conference system. The authors of the submitted papers covered 16 countries worldwide and there were over 60 authors in the conference proceedings. The technical sessions were divided into five topical categories. Technical highlights included a keynote speech by Michael Brudno (Canada Research Chair in Computational Biology) and plenary talks by Nikhil R. Pal, Sung-Bae Cho, Yaochu Jin, and David W. Ussery. In addition, three tutorials by Kwoh Chee Keong, Stijn Meganck and Philip Shaw were included with CSBio 2010 registration.
With all the material available in the field of artificial intelligence (AI) and soft computing-texts, monographs, and journal articles-there remains a serious gap in the literature. Until now, there has been no comprehensive resource accessible to a broad audience yet containing a depth and breadth of information that enables the reader to fully understand and readily apply AI and soft computing concepts.
Political issues people care about such as racism, climate change, and democracy take on new urgency and meaning in the light of technological developments such as AI. How can we talk about the politics of AI while moving beyond mere warnings and easy accusations? This is the first accessible introduction to the political challenges related to AI. Using political philosophy as a unique lens through which to explore key debates in the area, the book shows how various political issues are already impacted by emerging AI technologies: from justice and discrimination to democracy and surveillance. Revealing the inherently political nature of technology, it offers a rich conceptual toolbox that can guide efforts to deal with the challenges raised by what turns out to be not only artificial intelligence but also artificial power. This timely and original book will appeal to students and scholars in philosophy of technology and political philosophy, as well as tech developers, innovation leaders, policy makers, and anyone interested in the impact of technology on society.
This book applies both industrial engineering and computational intelligence to demonstrate intelligent machines that solve real-world problems in various smart environments. The title presents fundamental concepts and the latest advances in Multi-Criteria Decision Making (MCDM) techniques and their application to smart environments. Though managers and engineers often use multi-criteria analysis in making complex decisions, many core problems are too difficult to model mathematically or have simply not yet been modelled. In response, as well as AI-based approaches, this book covers various optimization techniques, decision analytics and data science in applying soft computing techniques to a defined set of smart environments, including smart and sustainable cities, disaster response systems and smart campuses. This state-of-the-art book will be essential reading for both undergraduate and graduate students, researchers, practitioners and decision makers interested in advanced MCDM techniques for management and engineering in relation to smart environments.
Provides a comprehensive review on new swarm intelligence Offers practical implementation of PSO with MATLAB code Presents statistical analysis techniques so that researchers can analyze their own experiment design Discusses swarm intelligence algorithms in social sector and oil and gas industries Covers recent findings and the implementation techniques to Machine Learning |
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